Table of Contents
Table of Contents
This manual applies to OProfile version 0.9.1cvs. OProfile is a profiling system for Linux 2.2/2.4/2.6 systems on a number of architectures. It is capable of profiling all parts of a running system, from the kernel (including modules and interrupt handlers) to shared libraries to binaries. It runs transparently in the background collecting information at a low overhead. These features make it ideal for profiling entire systems to determine bottle necks in real-world systems.
Many CPUs provide "performance counters", hardware registers that can count "events"; for example, cache misses, or CPU cycles. OProfile provides profiles of code based on the number of these occurring events: repeatedly, every time a certain (configurable) number of events has occurred, the PC value is recorded. This information is aggregated into profiles for each binary image.
Some hardware setups do not allow OProfile to use performance counters: in these cases, no events are available, and OProfile operates in timer/RTC mode, as described in later chapters.
OProfile is useful in a number of situations. You might want to use OProfile when you :
need low overhead
cannot use highly intrusive profiling methods
need to profile interrupt handlers
need to profile an application and its shared libraries
need to capture the performance behaviour of entire system
want to examine hardware effects such as cache misses
want detailed source annotation
want instruction-level profiles
want call-graph profiles
OProfile is not a panacea. OProfile might not be a complete solution when you :
require call graph profiles on platforms other than 2.6/x86
don't have root permissions
require 100% instruction-accurate profiles
need function call counts or an interstitial profiling API
cannot tolerate any disturbance to the system whatsoever
need to profile interpreted or dynamically compiled code such as Java or Python
OProfile uses a kernel module that can be compiled for
2.2.11 or later and 2.4. Versions 2.4.10 or above are recommended, and required if you use the
boot-time kernel option nosmp
. 2.6 kernels are supported with the in-kernel
OProfile driver. Note that only 32-bit x86 and IA64 are supported on 2.2/2.4 kernels.
PPC64 processors (Power4/Power5/PPC970) require a recent (> 2.6.5) kernel with the line
#define PV_970
present in include/asm-ppc64/processor.h
.
You should have installed modutils 2.4.6 or higher (in fact earlier versions work well in almost all cases).
For Intel IA32, a CPU with either a P6 generation or Pentium 4 core is required. In marketing terms this translates to anything between an Intel Pentium Pro (not Pentium Classics) and a Pentium 4 / Xeon, including all Celerons. The AMD Athlon, and Duron CPUs are also supported. Other IA32 CPU types only support the RTC mode of OProfile; please see later in this manual for details. Hyper-threaded Pentium IVs are not supported in 2.4. For 2.4 kernels, the Intel IA-64 CPUs are also supported. For 2.6 kernels, there is additionally support for Alpha processors, MIPS, ARM, x86-64, sparc64, ppc64, and, in timer mode, PA-RISC and s390.
SMP machines are fully supported.
These libraries are required : popt
, bfd
,
liberty
(debian users: libiberty is provided in binutils-dev package), dl
,
plus the standard C++ libraries.
The opcontrol script requires bash version 2 at least to be installed
as /bin/bash
or /bin/bash2
The use of the GUI to start the profiler requires the Qt 2
library. Qt 3
should
also work.
Probably not too strenuous a requirement, but older A.OUT binaries/libraries are not supported.
OK, so it's not really a requirement, but I wish it was...
There is a web page (which you may be reading now) at http://oprofile.sf.net/.
You can download a source tarball or get anonymous CVS at the sourceforge page, http://sf.net/projects/oprofile/.
There is a low-traffic OProfile-specific mailing list, details at http://sf.net/mail/?group_id=16191.
There is a bug tracker for OProfile at SourceForge, http://sf.net/tracker/?group_id=16191&atid=116191.
Several OProfile developers and users sometimes hang out on channel #oprofile on the freenode network.
First you need to build OProfile and install it. ./configure, make, make install is often all you need, but note these arguments to ./configure :
--with-linux
Use this option to specify the location of the kernel source tree you wish to compile against. The kernel module is built against this source and will only work with a running kernel built from the same source with exact same options, so it is important you specify this option if you need to.
--with-kernel-support
Use this option with 2.6 and above kernels to indicate the kernel provides the OProfile device driver.
--with-qt-dir/includes/libraries
Specify the location of Qt headers and libraries. It defaults to searching in
$QTDIR
if these are not specified.
--enable-abi
Activate code within the OProfile sample collection daemon
oprofiled which records information about the binary
format of sample files in /var/lib/oprofile/abi
, to
permit their transport between hosts using the
opimport utility. See opimport
. This option is primarily intended for embedded
systems or remote analysis of production machines; if you will be
performing all sample analysis on the same machine as you are profiling,
it is safe to omit this option.
--disable-werror
Development versions of OProfile build by
default with -Werror
. This option turns
-Werror
off.
--disable-optimization
Disable the -O2
compiler flag
(useful if you discover an OProfile bug and want to give a useful
back-trace etc.)
You'll need to have a configured kernel source for the current kernel to build the module for 2.4 kernels. Since all distributions provide different kernels it's unlikely the running kernel match the configured source you installed. The safest way is to recompile your own kernel, run it and compile oprofile. It is also recommended that if you have a uniprocessor machine, you enable the local APIC / IO_APIC support for your kernel (this is automatically enabled for SMP kernels). With many BIOS, kernel >= 2.6.9 and UP kernel it's not sufficient to enable the local APIC you must also turn it on explicitely at boot time by providing "lapic" option to the kernel. On machines with power management, such as laptops, the power management must be turned off when using OProfile with 2.4 kernels. The power management software in the BIOS cannot handle the non-maskable interrupts (NMIs) used by OProfile for data collection. If you use the NMI watchdog, be aware that the watchdog is disabled when profiling starts, and not re-enabled until the OProfile module is removed (or, in 2.6, when OProfile is not running). If you compile OProfile for a 2.2 kernel you must be root to compile the module. If you are using 2.6 kernels or higher, you do not need kernel source, as long as the OProfile driver is enabled; additionally, you should not need to disable power management.
Please note that you must save or have available the vmlinux
file
generated during a kernel compile, as OProfile needs it (you can use
--no-vmlinux
, but this will prevent kernel profiling).
Table of Contents
Before you can use OProfile, you must set it up. The minimum setup required for this
is to tell OProfile where the vmlinux
file corresponding to the
running kernel is, for example :
opcontrol --vmlinux=/boot/vmlinux-`uname -r` |
If you don't want to profile the kernel itself,
you can tell OProfile you don't have a vmlinux
file :
opcontrol --no-vmlinux |
Now we are ready to start the daemon (oprofiled) which collects the profile data :
opcontrol --start |
When I want to stop profiling, I can do so with :
opcontrol --shutdown |
Note that unlike gprof, no instrumentation (-pg
and -a
options to gcc)
is necessary.
Periodically (or on opcontrol --shutdown or opcontrol --dump)
the profile data is written out into the /var/lib/oprofile/samples
directory.
These profile files cover shared libraries, applications, the kernel (vmlinux), and kernel modules.
You can clear the profile data (at any time) with opcontrol --reset.
You can get summaries of this data in a number of ways at any time. To get a summary of data across the entire system for all of these profiles, you can do :
opreport |
Or to get a more detailed summary, for a particular image, you can do something like :
opreport -l /boot/vmlinux-`uname -r` |
There are also a number of other ways of presenting the data, as described later in this manual. Note that OProfile will choose a default profiling setup for you. However, there are a number of options you can pass to opcontrol if you need to change something, also detailed later.
This section gives a brief description of the available OProfile utilities and their purpose.
ophelp
This utility lists the available events and short descriptions.
opcontrol
Used for controlling the OProfile data collection, discussed in Chapter 3, Controlling the profiler.
opreport
This is the main tool for retrieving useful profile data, described in Section 2, “Image summaries and symbol summaries (opreport)”.
opannotate
This utility can be used to produce annotated source, assembly or mixed source/assembly. Source level annotation is available only if the application was compiled with debugging symbols. See Section 3, “Outputting annotated source (opannotate)”.
opgprof
This utility can output gprof-style data files for a binary, for use with gprof -p. See Section 4, “gprof-compatible output (opgprof)”.
oparchive
This utility can be used to collect executables, debuginfo, and sample files and copy the files into an archive. The archive is self-contained and can be moved to another machine for further analysis. See Section 5, “Archiving measurements (oparchive)”.
opimport
This utility converts sample database files from a foreign binary format (abi) to
the native format. This is useful only when moving sample files between hosts,
for analysis on platforms other than the one used for collection. The abi format
of the file to be imported is described in a text file located in
/var/lib/oprofile/abi
, if the --enable-abi
configure-time option was enabled. Furthermore, the opimport
tool is not built unless --enable-abi
is given. See --enable-abi
.
Table of Contents
In this section we describe the configuration and control of the profiling system with opcontrol in more depth. The opcontrol script has a default setup, but you can alter this with the options given below. In particular, if your hardware supports performance counters, you can configure them. There are a number of counters (for example, counter 0 and counter 1 on the Pentium III). Each of these counters can be programmed with an event to count, such as cache misses or MMX operations. The event chosen for each counter is reflected in the profile data collected by OProfile: functions and binaries at the top of the profiles reflect that most of the chosen events happened within that code.
Additionally, each counter has a "count" value: this corresponds to how detailed the profile is. The lower the value, the more frequently profile samples are taken. A counter can choose to sample only kernel code, user-space code, or both (both is the default). Finally, some events have a "unit mask" - this is a value that further restricts the types of event that are counted. The event types and unit masks for your CPU are listed by opcontrol --list-events.
The opcontrol script provides the following actions :
--init
Loads the OProfile module if required and makes the OProfile driver interface available.
--setup
Followed by list arguments for profiling set up. List of arguments
saved in /root/.oprofile/daemonrc
.
Giving this option is not necessary; you can just directly pass one
of the setup options, e.g. opcontrol --no-vmlinux.
--status
Show configuration information.
--start-daemon
Start the oprofile daemon without starting actual profiling. The profiling
can then be started using --start
. This is useful for avoiding
measuring the cost of daemon startup, as --start
is a simple
write to a file in oprofilefs. Not available in 2.2/2.4 kernels.
--start
Start data collection with either arguments provided by --setup
or information saved in /root/.oprofile/daemonrc
. Specifying
the addition --verbose
makes the daemon generate lots of debug data
whilst it is running.
--dump
Force a flush of the collected profiling data to the daemon.
--stop
Stop data collection (this separate step is not possible with 2.2 or 2.4 kernels).
--shutdown
Stop data collection and kill the daemon.
--reset
Clears out data from current session, but leaves saved sessions.
--save=
session_name
Save data from current session to session_name.
--deinit
Shuts down daemon. Unload the OProfile module and oprofilefs.
--list-events
List event types and unit masks.
--help
Generate usage messages.
There are a number of possible settings, of which, only
--vmlinux
(or --no-vmlinux
)
is required. These settings are stored in ~/.oprofile/daemonrc
.
--buffer-size=
num
Number of samples in kernel buffer.
--cpu-buffer-size=
num
Number of samples in kernel per-cpu buffer (2.6 only). If you profile at high rate it can help to increase this if the log file show excessive count of sample lost cpu buffer overflow.
--event=
[eventspec]
Use the given performance counter event to profile. See Section 1.2, “Specifying performance counter events” below.
--separate=
[none,lib,kernel,thread,cpu,all]
By default, every profile is stored in a single file. Thus, for example,
samples in the C library are all accredited to the /lib/libc.o
profile. However, you choose to create separate sample files by specifying
one of the below options.
none
|
No profile separation (default) |
lib
|
Create per-application profiles for libraries |
kernel
|
Create per-application profiles for the kernel and kernel modules |
thread
|
Create profiles for each thread and each task |
cpu
|
Create profiles for each CPU |
all
|
All of the above options |
Note that --separate=kernel
also turns on --separate=lib
.
When using --separate=kernel
, samples in hardware interrupts, soft-irqs, or other
asynchronous kernel contexts are credited to the task currently running. This means you will see
seemingly nonsense profiles such as /bin/bash
showing samples for the PPP modules,
etc.
On 2.2/2.4 only kernel threads already started when profiling begins are correctly profiled; newly started kernel thread samples are credited to the vmlinux (kernel) profile.
Using --separate=thread
creates a lot
of sample files if you leave OProfile running for a while; it's most
useful when used for short sessions, or when using image filtering.
--callgraph=
#depth
Enable call-graph sample collection with a maximum depth. Use 0 to disable callgraph profiling. Currently this requires a recent 2.6 kernel, and x86.
--image=
image,[images]|"all"
Image filtering. If you specify one or more absolute
paths to binaries, OProfile will only produce profile results for those
binary images. This is useful for restricting the sometimes voluminous
output you may get otherwise, especially with
--separate=thread
. Note that if you are using
--separate=lib
or
--separate=kernel
, then if you specification an
application binary, the shared libraries and kernel code
are included. Specify the value
"all" to profile everything (the default).
--vmlinux=
file
vmlinux kernel image.
--no-vmlinux
Use this when you don't have a kernel vmlinux file, and you don't want to profile the kernel. This still counts the total number of kernel samples, but can't give symbol-based results for the kernel or any modules.
Here, we have a Pentium III running at 800MHz, and we want to look at where data memory references are happening most, and also get results for CPU time.
# opcontrol --event=CPU_CLK_UNHALTED:400000 --event=DATA_MEM_REFS:10000 # opcontrol --vmlinux=/boot/2.6.0/vmlinux # opcontrol --start |
Here, we have an Intel laptop without support for performance counters, running on 2.4 kernels.
# ophelp -r CPU with RTC device # opcontrol --vmlinux=/boot/2.4.13/vmlinux --event=RTC_INTERRUPTS:1024 # opcontrol --start |
If we're running 2.6 kernels, we can use --start-daemon
to avoid
the profiler startup affecting results.
# opcontrol --vmlinux=/boot/2.6.0/vmlinux # opcontrol --start-daemon # my_favourite_benchmark --init # opcontrol --start ; my_favourite_benchmark --run ; opcontrol --stop |
Here, we want to see a profile of the OProfile daemon itself, including when it was running inside the kernel driver, and its use of shared libraries.
# opcontrol --separate=kernel --vmlinux=/boot/2.6.0/vmlinux # opcontrol --start # my_favourite_stress_test --run # opreport -l -p /lib/modules/2.6.0/kernel /usr/local/bin/oprofiled |
It can often be useful to split up profiling data into several different time periods. For example, you may want to collect data on an application's startup separately from the normal runtime data. You can use the simple command opcontrol --save to do this. For example :
# opcontrol --save=blah |
will create a sub-directory in /var/lib/oprofile/samples
containing the samples
up to that point (the current session's sample files are moved into this
directory). You can then pass this session name as a parameter to the post-profiling
analysis tools, to only get data up to the point you named the
session. If you do not want to save a session, you can do
rm -rf /var/lib/oprofile/samples/sessionname or, for the
current session, opcontrol --reset.
The --event
option to opcontrol
takes a specification that indicates how the details of each
hardware performance counter should be setup. If you want to
revert to OProfile's default setting (--event
is strictly optional), use --event=default
.
You can pass multiple event specifications. OProfile will allocate
hardware counters as necessary. Note that some combinations are not
allowed by the CPU; running opcontrol --list-events gives the details
of each event. The event specification is a colon-separated string
of the form name:count:unitmask:kernel:user
as described in this table:
For the PowerPC platforms, all events specified must be in the same group; i.e., the group number
appended to the event name (e.g. <some-event-name>_GRP9
) must be the same.
name
|
The symbolic event name, e.g. CPU_CLK_UNHALTED |
count
|
The counter reset value, e.g. 100000 |
unitmask
|
The unit mask, as given in the events list, e.g. 0x0f |
kernel
|
Whether to profile kernel code |
user
|
Whether to profile userspace code |
The last three values are optional, if you omit them (e.g. --event=DATA_MEM_REFS:30000
),
they will be set to the default values (a unit mask of 0, and profiling both kernel and
userspace code). Note that some events require a unit mask.
If OProfile is using RTC mode, and you want to alter the default counter value,
you can use something like --event=RTC_INTERRUPTS:2048
. Note the last
three values here are ignored.
If OProfile is using timer-interrupt mode, there is no configuration possible.
The table below lists the events selected by default
(--event=default
) for the various computer architectures:
Processor | cpu_type | Default event |
Alpha EV4 | alpha/ev4 | CYCLES:100000:0:1:1 |
Alpha EV5 | alpha/ev5 | CYCLES:100000:0:1:1 |
Alpha PCA56 | alpha/pca56 | CYCLES:100000:0:1:1 |
Alpha EV6 | alpha/ev6 | CYCLES:100000:0:1:1 |
Alpha EV67 | alpha/ev67 | CYCLES:100000:0:1:1 |
ARM/XScale PMU1 | arm/xscale1 | CPU_CYCLES:100000:0:1:1 |
ARM/XScale PMU2 | arm/xscale2 | CPU_CYCLES:100000:0:1:1 |
Athlon | i386/athlon | CPU_CLK_UNHALTED:100000:0:1:1 |
Pentium Pro | i386/ppro | CPU_CLK_UNHALTED:100000:0:1:1 |
Pentium II | i386/pii | CPU_CLK_UNHALTED:100000:0:1:1 |
Pentium III | i386/piii | CPU_CLK_UNHALTED:100000:0:1:1 |
Pentium M (P6 core) | i386/p6_mobile | CPU_CLK_UNHALTED:100000:0:1:1 |
Pentium 4 (non-HT) | i386/p4 | GLOBAL_POWER_EVENTS:100000:1:1:1 |
Pentium 4 (HT) | i386/p4-ht | GLOBAL_POWER_EVENTS:100000:1:1:1 |
Hammer | x86-64/hammer | CPU_CLK_UNHALTED:100000:0:1:1 |
Itanium | ia64/itanium | CPU_CYCLES:100000:0:1:1 |
Itanium 2 | ia64/itanium2 | CPU_CYCLES:100000:0:1:1 |
TIMER_INT | timer | None selectable |
IBM iseries | PowerPC 4/5/970 | CYCLES:10000:0:1:1 |
IBM pseries | PowerPC 4/5/970 | CYCLES:10000:0:1:1 |
IBM s390 | timer | None selectable |
IBM s390x | timer | None selectable |
The oprof_start application provides a convenient way to start the profiler. Note that oprof_start is just a wrapper around the opcontrol script, so it does not provide more services than the script itself.
After oprof_start is started you can select the event type for each counter; the sampling rate and other related parameters are explained in Section 1, “Using opcontrol”. The "Configuration" section allows you to set general parameters such as the buffer size, kernel filename etc. The counter setup interface should be self-explanatory; Section 3.1, “Hardware performance counters” and related links contain information on using unit masks.
A status line shows the current status of the profiler: how long it has been running, and the average number of interrupts received per second and the total, over all processors. Note that quitting oprof_start does not stop the profiler.
Your configuration is saved in the same file as opcontrol uses; that is,
~/.oprofile/daemonrc
.
Your CPU type may not include the requisite support for hardware performance counters, in which case you must use OProfile in RTC mode in 2.4 (see Section 3.2, “OProfile in RTC mode”), or timer mode in 2.6 (see Section 3.3, “OProfile in timer interrupt mode”). You do not really need to read this section unless you are interested in using events other than the default event chosen by OProfile.
The Intel hardware performance counters are detailed in the Intel IA-32 Architecture Manual, Volume 3, available from http://developer.intel.com/. The AMD Athlon/Duron implementation is detailed in http://www.amd.com/us-en/assets/content_type/white_papers_and_tech_docs/22007.pdf. For PowerPC64 processors in IBM iSeries and pSeries systems, processor documentation is available at http://www-306.ibm.com/chips/techlib/techlib.nsf/productfamilies/PowerPC. (For example, the specific publication containing information on the performance monitor unit for the PowerPC970 is "IBM PowerPC 970FX RISC Microprocessor User's Manual.") These processors are capable of delivering an interrupt when a counter overflows. This is the basic mechanism on which OProfile is based. The delivery mode is NMI, so blocking interrupts in the kernel does not prevent profiling. When the interrupt handler is called, the current PC value and the current task are recorded into the profiling structure. This allows the overflow event to be attached to a specific assembly instruction in a binary image. The daemon receives this data from the kernel, and writes it to the sample files.
If we use an event such as CPU_CLK_UNHALTED
or INST_RETIRED
(GLOBAL_POWER_EVENTS
or INSTR_RETIRED
, respectively, on the Pentium 4), we can
use the overflow counts as an estimate of actual time spent in each part of code. Alternatively we can profile interesting
data such as the cache behaviour of routines with the other available counters.
However there are several caveats. First, there are those issues listed in the Intel manual. There is a delay between the counter overflow and the interrupt delivery that can skew results on a small scale - this means you cannot rely on the profiles at the instruction level as being perfectly accurate. If you are using an "event-mode" counter such as the cache counters, a count registered against it doesn't mean that it is responsible for that event. However, it implies that the counter overflowed in the dynamic vicinity of that instruction, to within a few instructions. Further details on this problem can be found in Chapter 5, Interpreting profiling results and also in the Digital paper "ProfileMe: A Hardware Performance Counter".
Each counter has several configuration parameters. First, there is the unit mask: this simply further specifies what to count. Second, there is the counter value, discussed below. Third, there is a parameter whether to increment counts whilst in kernel or user space. You can configure these separately for each counter.
After each overflow event, the counter will be re-initialized such that another overflow will occur after this many events have been counted. Thus, higher values mean less-detailed profiling, and lower values mean more detail, but higher overhead. Picking a good value for this parameter is, unfortunately, somewhat of a black art. It is of course dependent on the event you have chosen. Specifying too large a value will mean not enough interrupts are generated to give a realistic profile (though this problem can be ameliorated by profiling for longer). Specifying too small a value can lead to higher performance overhead.
This section applies to 2.2/2.4 kernels only.
Some CPU types do not provide the needed hardware support to use the hardware performance counters. This includes some laptops, classic Pentiums, and other CPU types not yet supported by OProfile (such as Cyrix). On these machines, OProfile falls back to using the real-time clock interrupt to collect samples. This interrupt is also used by the rtc module: you cannot have both the OProfile and rtc modules loaded nor the rtc support compiled in the kernel.
RTC mode is less capable than the hardware counters mode; in particular, it is unable to profile sections of the kernel where interrupts are disabled. There is just one available event, "RTC interrupts", and its value corresponds to the number of interrupts generated per second (that is, a higher number means a better profiling resolution, and higher overhead). The current implementation of the real-time clock supports only power-of-two sampling rates from 2 to 4096 per second. Other values within this range are rounded to the nearest power of two.
Setting the value from the GUI should be straightforward. On the command line, you need to specify the event to opcontrol, e.g. :
opcontrol --event=RTC_INTERRUPTS:256
This section applies to 2.6 kernels and above only.
In 2.6 kernels on CPUs without OProfile support for the hardware performance counters, the driver falls back to using the timer interrupt for profiling. Like the RTC mode in 2.4 kernels, this is not able to profile code that has interrupts disabled. Note that there are no configuration parameters for setting this, unlike the RTC and hardware performance counter setup.
You can force use of the timer interrupt by using the timer=1
module
parameter (or oprofile.timer=1
on the boot command line if OProfile is
built-in).
The Pentium 4 / Xeon performance counters are organized around 3 types of model specific registers (MSRs): 45 event selection control registers (ESCRs), 18 counter configuration control registers (CCCRs) and 18 counters. ESCRs describe a particular set of events which are to be recorded, and CCCRs bind ESCRs to counters and configure their operation. Unfortunately the relationship between these registers is quite complex; they cannot all be used with one another at any time. There is, however, a subset of 8 counters, 8 ESCRs, and 8 CCCRs which can be used independently of one another, so OProfile only accesses those registers, treating them as a bank of 8 "normal" counters, similar to those in the P6 or Athlon families of CPU.
There is currently no support for Precision Event-Based Sampling (PEBS), nor any advanced uses of the Debug Store (DS). Current support is limited to the conservative extension of OProfile's existing interrupt-based model described above. Performance monitoring hardware on Pentium 4 / Xeon processors with Hyperthreading enabled (multiple logical processors on a single die) is not supported in 2.4 kernels (you can use OProfile if you disable hyper-threading, though).
The Itanium 2 performance monitoring unit (PMU) organizes the counters as four pairs of performance event monitoring registers. Each pair is composed of a Performance Monitoring Configuration (PMC) register and Performance Monitoring Data (PMD) register. The PMC selects the performance event being monitored and the PMD determines the sampling interval. The IA64 Performance Monitoring Unit (PMU) triggers sampling with maskable interrupts. Thus, samples will not occur in sections of the IA64 kernel where interrupts are disabled.
None of the advance features of the Itanium 2 performance monitoring unit such as opcode matching, address range matching, or precise event sampling are supported by this version of OProfile. The Itanium 2 support only maps OProfile's existing interrupt-based model to the PMU hardware.
The performance monitoring unit (PMU) for the PowerPC 64-bit processors consists of between 6 and 8 counters (depending on the model), plus three special purpose registers used for programming the counters -- MMCR0, MMCR1, and MMCRA. Advanced features such as instruction matching and thresholding are not supported by this version of OProfile.
OProfile is a low-level profiler which allow continuous profiling with a low-overhead cost. If too low a count reset value is set for a counter, the system can become overloaded with counter interrupts, and seem as if the system has frozen. Whilst some validation is done, it is not foolproof.
This can happen as follows: When the profiler count reaches zero an NMI handler is called which stores the sample values in an internal buffer, then resets the counter to its original value. If the count is very low, a pending NMI can be sent before the NMI handler has completed. Due to the priority of the NMI, the local APIC delivers the pending interrupt immediately after completion of the previous interrupt handler, and control never returns to other parts of the system. In this way the system seems to be frozen.
If this happens, it will be impossible to bring the system back to a workable state.
There is no way to provide real security against this happening, other than making sure to use a reasonable value
for the counter reset. For example, setting CPU_CLK_UNHALTED
event type with a ridiculously low reset count (e.g. 500)
is likely to freeze the system.
In short : Don't try a foolish sample count value. Unfortunately the definition of a foolish value is really dependent on the event type - if ever in doubt, e-mail
Table of Contents
OK, so the profiler has been running, but it's not much use unless we can get some data out. Fairly often, OProfile does a little too good a job of keeping overhead low, and no data reaches the profiler. This can happen on lightly-loaded machines. Remember you can force a dump at any time with :
opcontrol --dump
Remember to do this before complaining there is no profiling data ! Now that we've got some data, it has to be processed. That's the job of opreport, opannotate, or opgprof.
All of the analysis tools take a profile specification. This is a set of definitions that describe which actual profiles should be examined. The simplest profile specification is empty: this will match all the available profile files for the current session (this is what happens when you do opreport).
Specification parameters are of the form name:value[,value]
.
For example, if I wanted to get a combined symbol summary for
/bin/myprog
and /bin/myprog2
,
I could do opreport -l image:/bin/myprog,/bin/myprog2.
As a special case, you don't actually need to specify the image:
part here: anything left on the command line is assumed to be an
image:
name. Similarly, if no session:
is specified, then session:current
is assumed ("current"
is a special name of the current / last profiling session).
In addition to the comma-separated list shown above, some of the
specification parameters can take glob-style
values. For example, if I want to see image summaries for all
binaries profiled in /usr/bin/
, I could do
opreport image:/usr/bin/\*. Note the necessity
to escape the special character from the shell.
For opreport, profile specifications can be used to define two profiles, giving differential output. This is done by enclosing each of the two specifications within curly braces, as shown in the examples below. Any specifications outside of curly braces are shared across both.
Image summaries for all profiles with DATA_MEM_REFS
samples in the saved session called "stresstest" :
# opreport session:stresstest event:DATA_MEM_REFS |
Symbol summary for the application called "test_sym53c8xx,9xx". Note the
escaping is necessary as image:
takes a comma-separated list.
# opreport -l ./test/test_sym53c8xx\,9xx |
Image summaries for all binaries in the test
directory,
excepting boring-test
:
# opreport image:./test/\* image-exclude:./test/boring-test |
Differential profile of a binary stored in two archives :
# opreport -l /bin/bash { archive:./orig } { archive:./new } |
Differential profile of an archived binary with the current session :
# opreport -l /bin/bash { archive:./orig } { } |
archive:
archivepath
A path to an archive made with oparchive. Absence of this tag, unlike others, means "the current system", equivalent to specifying "archive:".
session:
sessionlist
A comma-separated list of session names to resolve in. Absence of this tag, unlike others, means "the current session", equivalent to specifying "session:current".
session-exclude:
sessionlist
A comma-separated list of sessions to exclude.
image:
imagelist
A comma-separated list of image names to resolve. Each entry may be relative path, glob-style name, or full path, e.g.
opreport 'image:/usr/bin/oprofiled,*op*,./opreport' |
image-exclude:
imagelist
Same as image:
, but the matching images are excluded.
lib-image:
imagelist
Same as image:
, but only for images that are for
a particular primary binary image (namely, an application). This only
makes sense to use if you're using --separate
.
This includes kernel modules and the kernel when using
--separate=kernel
.
lib-image-exclude:
imagelist
Same as lib-image:
, but the matching images
are excluded.
event:
eventlist
The symbolic event name to match on, e.g. event:DATA_MEM_REFS
.
You can pass a list of events for side-by-side comparison with opreport.
When using the timer interrupt, the event is always "TIMER".
count:
eventcountlist
The event count to match on, e.g. event:DATA_MEM_REFS count:30000
.
Note that this value refers to the setting used for opcontrol
only, and has nothing to do with the sample counts in the profile data
itself.
You can pass a list of events for side-by-side comparison with opreport.
When using the timer interrupt, the count is always 0 (indicating it cannot be set).
unit-mask:
masklist
The unit mask value of the event to match on, e.g. unit-mask:1
.
You can pass a list of events for side-by-side comparison with opreport.
cpu:
cpulist
Only consider profiles for the given numbered CPU (starting from zero). This is only useful when using CPU profile separation.
tgid:
pidlist
Only consider profiles for the given task groups. Unless some program is using threads, the task group ID of a process is the same as its process ID. This option corresponds to the POSIX notion of a thread group. This is only useful when using per-process profile separation.
tid:
tidlist
Only consider profiles for the given threads. When using
recent thread libraries, all threads in a process share the
same task group ID, but have different thread IDs. You can
use this option in combination with tgid:
to
restrict the results to particular threads within a process.
This is only useful when using per-process profile separation.
Each session's sample files can be found in the /var/lib/oprofile/samples/
directory.
These are used, along with the binary image files, to produce human-readable data.
In some circumstances (kernel modules in an initrd, or modules on 2.6 kernels), OProfile
will not be able to find the binary images. All the tools have an --image-path
option to which you can pass a comma-separated list of alternate paths to search. For example,
I can let OProfile find my 2.6 modules by using --image-path /lib/modules/2.6.0/kernel/.
It is your responsibility to ensure that the correct images are found when using this
option.
Note that if a binary image changes after the sample file was created, you won't be able to get useful symbol-based data out. This situation is detected for you. If you replace a binary, you should make sure to save the old binary if you need to do comparative profiles.
When attempting to get output, you may see the error :
error: no sample files found: profile specification too strict ? |
What this is saying is that the profile specification you passed in, when matched against the available sample files, resulted in no matches. There are a number of reasons this might happen:
You specified a binary name, but spelt it wrongly. Check your spelling !
Make very sure that OProfile was actually up and running when you ran the binary.
Remember OProfile is a statistical profiler - you're not guaranteed to get samples for short-running programs. You can help this by using a lower count for the performance counter, so there are a lot more samples taken per second.
Similarly, if the binary spends little time in the main binary image itself, with most of it spent in shared libraries it uses, you might not see any samples for the binary image itself. You can check this by using opcontrol --separate=lib before the profiling session, so opreport and friends show the library profiles on a per-application basis.
For example, you specified something like tgid:3433
,
but no task with that group ID ever ran the code.
If you're using a particular event counter, for example counting MMX operations, the code might simply have not generated any events in the first place. Verify the code you're profiling does what you expect it to.
If you're using 2.6 kernels, and trying to get reports for a kernel
module, make sure to use the -p
option, and specify the
module name with the .ko
extension. Check if the module is one loaded from initrd.
The opreport utility is the primary utility you will use for getting formatted data out of OProfile. It produces two types of data: image summaries and symbol summaries. An image summary lists the number of samples for individual binary images such as libraries or applications. Symbol summaries provide per-symbol profile data. In the following example, we're getting an image summary for the whole system:
$ opreport --long-filenames CPU: PIII, speed 863.195 MHz (estimated) Counted CPU_CLK_UNHALTED events (clocks processor is not halted) with a unit mask of 0x00 (No unit mask) count 23150 905898 59.7415 /usr/lib/gcc-lib/i386-redhat-linux/3.2/cc1plus 214320 14.1338 /boot/2.6.0/vmlinux 103450 6.8222 /lib/i686/libc-2.3.2.so 60160 3.9674 /usr/local/bin/madplay 31769 2.0951 /usr/local/oprofile-pp/bin/oprofiled 26550 1.7509 /usr/lib/libartsflow.so.1.0.0 23906 1.5765 /usr/bin/as 18770 1.2378 /oprofile 15528 1.0240 /usr/lib/qt-3.0.5/lib/libqt-mt.so.3.0.5 11979 0.7900 /usr/X11R6/bin/XFree86 11328 0.7471 /bin/bash ... |
If we had specified --symbols
in the previous command, we would have
gotten a symbol summary of all the images across the entire system. We can restrict this to only
part of the system profile; for example,
below is a symbol summary of the OProfile daemon. Note that as we used
opcontrol --separate=kernel, symbols from images that oprofiled
has used are also shown.
$ opreport -l `which oprofiled` 2>/dev/null | more CPU: PIII, speed 863.195 MHz (estimated) Counted CPU_CLK_UNHALTED events (clocks processor is not halted) with a unit mask of 0x00 (No unit mask) count 23150 vma samples % image name symbol name 0804be10 14971 28.1993 oprofiled odb_insert 0804afdc 7144 13.4564 oprofiled pop_buffer_value c01daea0 6113 11.5144 vmlinux __copy_to_user_ll 0804b060 2816 5.3042 oprofiled opd_put_sample 0804b4a0 2147 4.0441 oprofiled opd_process_samples 0804acf4 1855 3.4941 oprofiled opd_put_image_sample 0804ad84 1766 3.3264 oprofiled opd_find_image 0804a5ec 1084 2.0418 oprofiled opd_find_module 0804ba5c 741 1.3957 oprofiled odb_hash_add_node ... |
These are the two basic ways you are most likely to use regularly, but opreport can do a lot more than that, as described below.
--separate=
options
whilst profiling, there can be several separate profiles for
a single binary image within a session. Normally the output
will keep these images separated (so, for example, the image summary
output shows library image summaries on a per-application basis,
when using --separate=lib
).
Sometimes it can be useful to merge these results back together
before getting results. The --merge
option allows
you to do that.
event:
profile specifications, etc.
When using the opcontrol --callgraph
option, you can see what
functions are calling other functions in the output. Consider the
following program:
#include <string.h> #include <stdlib.h> #include <stdio.h> #define SIZE 500000 static int compare(const void *s1, const void *s2) { return strcmp(s1, s2); } static void repeat(void) { int i; char *strings[SIZE]; char str[] = "abcdefghijklmnopqrstuvwxyz"; for (i = 0; i < SIZE; ++i) { strings[i] = strdup(str); strfry(strings[i]); } qsort(strings, SIZE, sizeof(char *), compare); } int main() { while (1) repeat(); } |
When running with the call-graph option, OProfile will record the function stack every time it takes a sample. opreport --callgraph outputs an entry for each function, where each entry looks similar to:
samples % image name symbol name 197 0.1548 cg main 127036 99.8452 cg repeat 84590 42.5084 libc-2.3.2.so strfry 84590 66.4838 libc-2.3.2.so strfry [self] 39169 30.7850 libc-2.3.2.so random_r 3475 2.7312 libc-2.3.2.so __i686.get_pc_thunk.bx ------------------------------------------------------------------------------- |
Here the non-indented line is the function we're focussing upon
(strfry()
). This
line is the same as you'd get from a normal opreport
output.
Above the non-indented line we find the functions that called this
function (for example, repeat()
calls
strfry()
). The samples and percentage values here
refer to the number of times we took a sample where this call was found
in the stack; the percentage is relative to all other callers of the
function we're focussing on. Note that these values are
not call counts; they only reflect the call stack
every time a sample is taken; that is, if a call is found in the stack
at the time of a sample, it is recorded in this count.
Below the line are functions that are called by
strfry()
(called callees).
It's clear here that strfry()
calls
random_r()
. We also see a special entry with a
"[self]" marker. This records the normal samples for the function, but
the percentage becomes relative to all callees. This allows you to
compare time spent in the function itself compared to functions it
calls. Note that if a function calls itself, then it will appear in the
list of callees of itself, but without the "[self]" marker; so recursive
calls are still clearly separable.
You may have noticed that the output lists main()
as calling strfry()
, but it's clear from the source
that this doesn't actually happen. See Section 3, “Interpreting call-graph profiles” for an explanation.
Often, we'd like to be able to compare two profiles. For example, when analysing the performance of an application, we'd like to make code changes and examine the effect of the change. This is supported in opreport by giving a profile specification that identifies two different profiles. The general form is of:
$ opreport <shared-spec> { <first-profile> } { <second-profile> } |
For each of the profiles, the shared section is prefixed, and then the specification is analysed. The usual parameters work both within the shared section, and in the sub-specification within the curly braces.
A typical way to use this feature is with archives created with oparchive. Let's look at an example:
$ ./a $ oparchive -o orig ./a $ opcontrol --reset # edit and recompile a $ ./a # now compare the current profile of a with the archived profile $ opreport -xl ./a { archive:./orig } { } CPU: PIII, speed 863.233 MHz (estimated) Counted CPU_CLK_UNHALTED events (clocks processor is not halted) with a unit mask of 0x00 (No unit mask) count 100000 samples % diff % symbol name 92435 48.5366 +0.4999 a 54226 --- --- c 49222 25.8459 +++ d 48787 25.6175 -2.2e-01 b |
Note that we specified an empty second profile in the curly braces, as we wanted to use the current session; alternatively, we could have specified another archive, or a tgid etc. We specified the binary a in the shared section, so we matched that in both the profiles we're diffing.
As in the normal output, the results are sorted by the number of samples, and the percentage field represents the relative percentage of the symbol's samples in the second profile.
Notice the new column in the output. This value represents the
percentage change of the relative percent between the first and the
second profile: roughly, "how much more important this symbol is".
Looking at the symbol a()
, we can see that it took
roughly the same amount of the total profile in both the first and the
second profile. The function c()
was not in the new
profile, so has been marked with ---
. Note that the
sample value is the number of samples in the first profile; since we're
displaying results for the second profile, we don't list a percentage
value for it, as it would be meaningless. d()
is
new in the second profile, and consequently marked with
+++
.
When comparing profiles between different binaries, it should be clear that functions can change in terms of VMA and size. To avoid this problem, opreport considers a symbol to be the same if the symbol name, image name, and owning application name all match; any other factors are ignored. Note that the check for application name means that trying to compare library profiles between two different applications will not work as you might expect: each symbol will be considered different.
Many applications, typically ones involving dynamic compilation into machine code, have executable mappings that are not backed by an ELF file. opreport has basic support for showing the samples taken in these regions; for example:
$ opreport /usr/jre1.5.0/bin/java CPU: PIII, speed 863.195 MHz (estimated) Counted CPU_CLK_UNHALTED events (clocks processor is not halted) with a unit mask of 0x00 (No unit mask) count 100000 CPU_CLK_UNHALT...| samples| %| ------------------ 27344 100.000 java CPU_CLK_UNHALT...| samples| %| ------------------ 27236 99.605 anon (tgid:12135 range:0xb2cb8000-0xb2e80000) 108 0.3949 java |
Currently, there is no support for getting symbol-based summaries for
such regions. Note that, since such mappings are dependent upon
individual invocations of a binary, these mappings are always listed as
a dependent image, even when using --separate=none
.
Equally, the results are not affected by the --merge
option.
--accumulated / -a
Accumulate sample and percentage counts in the symbol list.
--callgraph / -c
Show callgraph information.
--debug-info / -g
Show source file and line for each symbol.
--demangle / -D none|normal|smart
none: no demangling. normal: use default demangler (default) smart: use pattern-matching to make C++ symbol demangling more readable.
--details / -d
Show per-instruction details for all selected symbols. Note that, for binaries without symbol information, the VMA values shown are raw file offsets for the image binary.
--exclude-dependent / -x
Do not include application-specific images for libraries, kernel modules and the kernel. This option only makes sense if the profile session used --separate.
--exclude-symbols / -e [symbols]
Exclude all the symbols in the given comma-separated list.
--global-percent / -%
Make all percentages relative to the whole profile.
--help / -? / --usage
Show help message.
--image-path / -p [paths]
Comma-separated list of additional paths to search for binaries. This is needed to find modules in kernels 2.6 and upwards.
--include-symbols / -i [symbols]
Only include symbols in the given comma-separated list.
--long-filenames / -l
Output full paths instead of basenames.
--merge / -m [lib,cpu,tid,tgid,unitmask,all]
Merge any profiles separated in a --separate session.
--no-header
Don't output a header detailing profiling parameters.
--output-file / -o [file]
Output to the given file instead of stdout.
--reverse-sort / -r
Reverse the sort from the default.
--show-address / -w
Show the VMA address of each symbol (off by default).
--sort / -s [vma,sample,symbol,debug,image]
Sort the list of symbols by, respectively, symbol address, number of samples, symbol name, debug filename and line number, binary image filename.
--symbols / -l
List per-symbol information instead of a binary image summary.
--threshold / -t [percentage]
Only output data for symbols that have more than the given percentage of total samples.
--verbose / -V [options]
Give verbose debugging output.
--version / -v
Show version.
The opannotate utility generates annotated source files or assembly listings, optionally
mixed with source.
If you want to see the source file, the profiled application needs to have debug information, and the source
must be available through this debug information. For GCC, you must use the -g
option
when you are compiling.
If the binary doesn't contain sufficient debug information, you can still
use opannotate --assembly
to get annotated assembly.
Note that for the reason explained in Section 3.1, “Hardware performance counters” the results can be inaccurate. The debug information itself can add other problems; for example, the line number for a symbol can be incorrect. Assembly instructions can be re-ordered and moved by the compiler, and this can lead to crediting source lines with samples not really "owned" by this line. Also see Chapter 5, Interpreting profiling results.
You can output the annotation to one single file, containing all the source found using the
--source
. You can use this in conjunction with --assembly
to get combined source/assembly output.
You can also output a directory of annotated source files that maintains the structure of the original sources. Each line in the annotated source is prepended with the samples for that line. Additionally, each symbol is annotated giving details for the symbol as a whole. An example:
$ opannotate --source --output-dir=annotated /usr/local/oprofile-pp/bin/oprofiled $ ls annotated/home/moz/src/oprofile-pp/daemon/ opd_cookie.h opd_image.c opd_kernel.c opd_sample_files.c oprofiled.c |
Line numbers are maintained in the source files, but each file has a footer appended describing the profiling details. The actual annotation looks something like this :
... :static uint64_t pop_buffer_value(struct transient * trans) 11510 1.9661 :{ /* pop_buffer_value total: 89901 15.3566 */ : uint64_t val; : 10227 1.7469 : if (!trans->remaining) { : fprintf(stderr, "BUG: popping empty buffer !\n"); : exit(EXIT_FAILURE); : } : : val = get_buffer_value(trans->buffer, 0); 2281 0.3896 : trans->remaining--; 2296 0.3922 : trans->buffer += kernel_pointer_size; : return val; 10454 1.7857 :} ... |
The first number on each line is the number of samples, whilst the second is the relative percentage of total samples.
Of course, opannotate needs to be able to locate the source files
for the binary image(s) in order to produce output. Some binary images have debug
information where the given source file paths are relative, not absolute. You can
specify search paths to look for these files (similar to gdb's
dir
command) with the --search-dirs
option.
Sometimes you may have a binary image which gives absolute paths for the source files,
but you have the actual sources elsewhere (commonly, you've installed an SRPM for
a binary on your system and you want annotation from an existing profile). You can
use the --base-dirs
option to redirect OProfile to look somewhere
else for source files. For example, imagine we have a binary generated from a source
file that is given in the debug information as /tmp/build/libfoo/foo.c
,
and you have the source tree matching that binary installed in /home/user/libfoo/
.
You can redirect OProfile to find foo.c
correctly like this :
$ opannotate --source --base-dirs=/tmp/build/libfoo/ --search-dirs=/home/user/libfoo/ --output-dir=annotated/ /lib/libfoo.so |
You can specify multiple (comma-separated) paths to both options.
--assembly / -a
Output annotated assembly. If this is combined with --source, then mixed source / assembly annotations are output.
--base-dirs / -b [paths]/
Comma-separated list of path prefixes. This can be used to point OProfile to a
different location for source files when the debug information specifies an
absolute path on your system for the source that does not exist. The prefix
is stripped from the debug source file paths, then searched in the search dirs
specified by --search-dirs
.
--demangle / -D none|normal|smart
none: no demangling. normal: use default demangler (default) smart: use pattern-matching to make C++ symbol demangling more readable.
--exclude-dependent / -x
Do not include application-specific images for libraries, kernel modules and the kernel. This option only makes sense if the profile session used --separate.
--exclude-file [files]
Exclude all files in the given comma-separated list of glob patterns.
--exclude-symbols / -e [symbols]
Exclude all the symbols in the given comma-separated list.
--help / -? / --usage
Show help message.
--image-path / -p [paths]
Comma-separated list of additional paths to search for binaries. This is needed to find modules in kernels 2.6 and upwards.
--include-file [files]
Only include files in the given comma-separated list of glob patterns.
--include-symbols / -i [symbols]
Only include symbols in the given comma-separated list.
--objdump-params [params]
Pass the given parameters as extra values when calling objdump.
--output-dir / -o [dir]
Output directory. This makes opannotate output one annotated file for each source file. This option can't be used in conjunction with --assembly.
--search-dirs / -d [paths]
Comma-separated list of paths to search for source files. This is useful to find source files when the debug information only contains relative paths.
--source / -s
Output annotated source. This requires debugging information to be available for the binaries.
--threshold / -t [percentage]
Only output data for symbols that have more than the given percentage of total samples.
--verbose / -V [options]
Give verbose debugging output.
--version / -v
Show version.
If you're familiar with the output produced by GNU gprof,
you may find opgprof useful. It takes a single binary
as an argument, and produces a gmon.out
file for use
with gprof -p. If call-graph profiling is enabled,
then this is also included.
$ opgprof `which oprofiled` # generates gmon.out file $ gprof -p `which oprofiled` | head Flat profile: Each sample counts as 1 samples. % cumulative self self total time samples samples calls T1/call T1/call name 33.13 206237.00 206237.00 odb_insert 22.67 347386.00 141149.00 pop_buffer_value 9.56 406881.00 59495.00 opd_put_sample 7.34 452599.00 45718.00 opd_find_image 7.19 497327.00 44728.00 opd_process_samples |
--help / -? / --usage
Show help message.
--image-path / -p [paths]
Comma-separated list of additional paths to search for binaries. This is needed to find modules in kernels 2.6 and upwards.
--output-filename / -o [file]
Output to the given file instead of the default, gmon.out
--threshold / -t [percentage]
Only output data for symbols that have more than the given percentage of total samples.
--verbose / -V [options]
Give verbose debugging output.
--version / -v
Show version.
The oparchive utility generates a directory populated with executable, debug, and oprofile sample files. This directory can be moved to another machine via tar and analyzed without further use of the data collection machine.
The following command would collect the sample files, the executables
associated with the sample files, and the debuginfo files associated
with the executables and copy them into
/tmp/current_data
:
# oparchive -o /tmp/current_data |
--help / -? / --usage
Show help message.
--exclude-dependent / -x
Do not include application-specific images for libraries, kernel modules and the kernel. This option only makes sense if the profile session used --separate.
--image-path / -p [paths]
Comma-separated list of additional paths to search for binaries. This is needed to find modules in kernels 2.6 and upwards.
--output-directory / -o [directory]
Output to the given directory. There is no default. This must be specified.
--verbose / -V [options]
Give verbose debugging output.
--version / -v
Show version.
Table of Contents
The standard caveats of profiling apply in interpreting the results from OProfile: profile realistic situations, profile different scenarios, profile for as long as a time as possible, avoid system-specific artifacts, don't trust the profile data too much. Also bear in mind the comments on the performance counters above - you cannot rely on totally accurate instruction-level profiling. However, for almost all circumstances the data can be useful. Ideally a utility such as Intel's VTUNE would be available to allow careful instruction-level analysis; go hassle Intel for this, not me ;)
This is an example of how the latency of delivery of profiling interrupts can impact the reliability of the profiling data. This is pretty much a worst-case-scenario example: these problems are fairly rare.
double fun(double a, double b, double c) { double result = 0; for (int i = 0 ; i < 10000; ++i) { result += a; result *= b; result /= c; } return result; } |
Here the last instruction of the loop is very costly, and you would expect the result reflecting that - but (cutting the instructions inside the loop):
$ opannotate -a -t 10 ./a.out 88 15.38% : 8048337: fadd %st(3),%st 48 8.391% : 8048339: fmul %st(2),%st 68 11.88% : 804833b: fdiv %st(1),%st 368 64.33% : 804833d: inc %eax : 804833e: cmp $0x270f,%eax : 8048343: jle 8048337 |
The problem comes from the x86 hardware; when the counter overflows the IRQ is asserted but the hardware has features that can delay the NMI interrupt: x86 hardware is synchronous (i.e. cannot interrupt during an instruction); there is also a latency when the IRQ is asserted, and the multiple execution units and the out-of-order model of modern x86 CPUs also causes problems. This is the same function, with annotation :
$ opannotate -s -t 10 ./a.out :double fun(double a, double b, double c) :{ /* _Z3funddd total: 572 100.0% */ : double result = 0; 368 64.33% : for (int i = 0 ; i < 10000; ++i) { 88 15.38% : result += a; 48 8.391% : result *= b; 68 11.88% : result /= c; : } : return result; :} |
The conclusion: don't trust samples coming at the end of a loop, particularly if the last instruction generated by the compiler is costly. This case can also occur for branches. Always bear in mind that samples can be delayed by a few cycles from its real position. That's a hardware problem and OProfile can do nothing about it.
OProfile uses non-maskable interrupts (NMI) on the P6 generation, Pentium 4, Athlon and Duron processors. These interrupts can occur even in section of the Linux where interrupts are disabled, allowing collection of samples in virtually all executable code. The RTC, timer interrupt mode, and Itanium 2 collection mechanisms use maskable interrupts. Thus, the RTC and Itanium 2 data collection mechanism have "sample shadows", or blind spots: regions where no samples will be collected. Typically, the samples will be attributed to the code immediately after the interrupts are re-enabled.
Your kernel is likely to support halting the processor when a CPU is idle. As
the typical hardware events like CPU_CLK_UNHALTED
do not
count when the CPU is halted, the kernel profile will not reflect the actual
amount of time spent idle. You can change this behaviour by booting with
the idle=poll
option, which uses a different idle routine. This
will appear as poll_idle()
in your kernel profile.
OProfile profiles kernel modules by default. However, there are a couple of problems
you may have when trying to get results. First, you may have booted via an initrd;
this means that the actual path for the module binaries cannot be determined automatically.
To get around this, you can use the -p
option to the profiling tools
to specify where to look for the kernel modules.
In 2.6, the information on where kernel module binaries are located has been removed.
This means OProfile needs guiding with the -p
option to find your
modules. Normally, you can just use your standard module top-level directory for this.
Note that due to this problem, OProfile cannot check that the modification times match;
it is your responsibility to make sure you do not modify a binary after a profile
has been created.
If you have run insmod or modprobe to insert a module
in a particular directory, it is important that you specify this directory with the
-p
option first, so that it over-rides an older module binary that might
exist in other directories you've specified with -p
. It is up to you
to make sure that these values are correct: 2.6 kernels simply do not provide enough
information for OProfile to get this information.
Sometimes the results from call-graph profiles may be different to what
you expect to see. The first thing to check is whether the target
binaries where compiled with frame pointers enabled (if the binary was
compiled using gcc's
-fomit-frame-pointer
option, you will not get
meaningful results). Note that as of this writing, the GCC developers
plan to disable frame pointers by default. The Linux kernel is built
without frame pointers by default; there is a configuration option you
can use to turn it on under the "Kernel Hacking" menu.
Often you may see a caller of a function that does not actually directly
call the function you're looking at (e.g. if a()
calls b()
, which in turn calls
c()
, you may see an entry for
a()->c()
). What's actually occurring is that we
are taking samples at the very start (or the very end) of
c()
; at these few instructions, we haven't yet
created the new function's frame, so it appears as if
a()
is calling directly into
c()
. Be careful not to be misled by these
entries.
Like the rest of OProfile, call-graph profiling uses a statistical approach; this means that sometimes a backtrace sample is truncated, or even partially wrong. Bear this in mind when examining results.
The compiler can introduce some pitfalls in the annotated source output. The optimizer can move pieces of code in such manner that two line of codes are interlaced (instruction scheduling). Also debug info generated by the compiler can show strange behavior. This is especially true for complex expressions e.g. inside an if statement:
if (a && .. b && .. c &&) |
here the problem come from the position of line number. The available debug
info does not give enough details for the if condition, so all samples are
accumulated at the position of the right brace of the expression. Using
opannotate -a
can help to show the real
samples at an assembly level.
The compiler generally needs to generate "glue" code across function calls, dependent on the particular function call conventions used. Additionally other things need to happen, like stack pointer adjustment for the local variables; this code is known as the function prologue. Similar code is needed at function return, and is known as the function epilogue. This will show up in annotations as samples at the very start and end of a function, where there is no apparent executable code in the source.
You may see that a function is credited with a certain number of samples, but the listing does not add up to the correct total. To pick a real example :
:internal_sk_buff_alloc_security(struct sk_buff *skb) 353 2.342% :{ /* internal_sk_buff_alloc_security total: 1882 12.48% */ : : sk_buff_security_t *sksec; 15 0.0995% : int rc = 0; : 10 0.06633% : sksec = skb->lsm_security; 468 3.104% : if (sksec && sksec->magic == DSI_MAGIC) { : goto out; : } : : sksec = (sk_buff_security_t *) get_sk_buff_memory(skb); 3 0.0199% : if (!sksec) { 38 0.2521% : rc = -ENOMEM; : goto out; 10 0.06633% : } : memset(sksec, 0, sizeof (sk_buff_security_t)); 44 0.2919% : sksec->magic = DSI_MAGIC; 32 0.2123% : sksec->skb = skb; 45 0.2985% : sksec->sid = DSI_SID_NORMAL; 31 0.2056% : skb->lsm_security = sksec; : : out: : 146 0.9685% : return rc; : 98 0.6501% :} |
Here, the function is credited with 1,882 samples, but the annotations
below do not account for this. This is usually because of inline functions -
the compiler marks such code with debug entries for the inline function
definition, and this is where opannotate annotates
such samples. In the case above, memset
is the most
likely candidate for this problem. Examining the mixed source/assembly
output can help identify such results.
When running opannotate, you may get a warning "some functions compiled without debug information may have incorrect source line attributions". In some rare cases, OProfile is not able to verify that the derived source line is correct (when some parts of the binary image are compiled without debugging information). Be wary of results if this warning appears.
Furthermore, for some languages the compiler can implicitly generate functions, such as default copy constructors. Such functions are labelled by the compiler as having a line number of 0, which means the source annotation can be confusing.
Depending on your compiler you can fall into the following problem:
struct big_object { int a[500]; }; int main() { big_object a, b; for (int i = 0 ; i != 1000 * 1000; ++i) b = a; return 0; } |
Compiled with gcc 3.0.4 the annotated source is clearly inaccurate:
:int main() :{ /* main total: 7871 100% */ : big_object a, b; : for (int i = 0 ; i != 1000 * 1000; ++i) : b = a; 7871 100% : return 0; :} |
The problem here is distinct from the IRQ latency problem; the debug line number information is not precise enough; again, looking at output of opannoatate -as can help.
:int main() :{ : big_object a, b; : for (int i = 0 ; i != 1000 * 1000; ++i) : 80484c0: push %ebp : 80484c1: mov %esp,%ebp : 80484c3: sub $0xfac,%esp : 80484c9: push %edi : 80484ca: push %esi : 80484cb: push %ebx : b = a; : 80484cc: lea 0xfffff060(%ebp),%edx : 80484d2: lea 0xfffff830(%ebp),%eax : 80484d8: mov $0xf423f,%ebx : 80484dd: lea 0x0(%esi),%esi : return 0; 3 0.03811% : 80484e0: mov %edx,%edi : 80484e2: mov %eax,%esi 1 0.0127% : 80484e4: cld 8 0.1016% : 80484e5: mov $0x1f4,%ecx 7850 99.73% : 80484ea: repz movsl %ds:(%esi),%es:(%edi) 9 0.1143% : 80484ec: dec %ebx : 80484ed: jns 80484e0 : 80484ef: xor %eax,%eax : 80484f1: pop %ebx : 80484f2: pop %esi : 80484f3: pop %edi : 80484f4: leave : 80484f5: ret |
So here it's clear that copying is correctly credited with of all the samples, but the line number information is misplaced. objdump -dS exposes the same problem. Note that maintaining accurate debug information for compilers when optimizing is difficult, so this problem is not suprising. The problem of debug information accuracy is also dependent on the binutils version used; some BFD library versions contain a work-around for known problems of gcc, some others do not. This is unfortunate but we must live with that, since profiling is pointless when you disable optimisation (which would give better debugging entries).
Often the assembler cannot generate debug information automatically. This means that you cannot get a source report unless you manually define the neccessary debug information; read your assembler documentation for how you might do that. The only debugging info needed currently by OProfile is the line-number/filename-VMA association. When profiling assembly without debugging info you can always get report for symbols, and optionally for VMA, through opreport -l or opreport -d, but this works only for symbols with the right attributes. For gas you can get this by
.globl foo .type foo,@function |
whilst for nasm you must use
GLOBAL foo:function ; [1] |
Note that OProfile does not need the global attribute, only the function attribute.
Another cause of apparent problems is the hidden cost of instructions. A very common example is two memory reads: one from L1 cache and the other from memory: the second memory read is likely to have more samples. There are many other causes of hidden cost of instructions. A non-exhaustive list: mis-predicted branch, TLB cache miss, partial register stall, partial register dependencies, memory mismatch stall, re-executed µops. If you want to write programs at the assembly level, be sure to take a look at the Intel and AMD documentation at http://developer.intel.com/ and http://www.amd.com/products/cpg/athlon/techdocs/.
Thanks to (in no particular order) : Arjan van de Ven, Rik van Riel, Juan Quintela, Philippe Elie, Phillipp Rumpf, Tigran Aivazian, Alex Brown, Alisdair Rawsthorne, Bob Montgomery, Ray Bryant, H.J. Lu, Jeff Esper, Will Cohen, Graydon Hoare, Cliff Woolley, Alex Tsariounov, Al Stone, Jason Yeh, Randolph Chung, Anton Blanchard, Richard Henderson, Andries Brouwer, Bryan Rittmeyer, Maynard P. Johnson, Richard Reich (rreich@rdrtech.com), Zwane Mwaikambo, Dave Jones, Charles Filtness; and finally Pulp, for "Intro".